lmsimp
commented
2 years ago Hello @daveshire, you need to pre-calculate the t-SNE matrix and then pass it to highlightOnPlot
An example below -
library(pRoloc)
library(pRolocdata)
## load some data
data("dunkley2006")
## make a some plots
set.seed(1)
tsne_coords <- plot2D(dunkley2006, method = "t-SNE", plot = FALSE)
pca_coords <- plot2D(dunkley2006, method = "PCA", plot = FALSE)
## some proteins to plot
fn <- featureNames(dunkley2006)[1:3]
fn
[1] "AT1G09210" "AT1G21750" "AT1G51760"
## plot the data and highlight the proteins
par(mfrow = c(1, 2))
## highlight on PCA
plot2D(pca_coords, method = "none", methargs = list(dunkley2006), main = "PCA")
highlightOnPlot(pca_coords, foi = fn, pch = 17, cex = 1.2)
## highlight the same proteins on t-SNE
plot2D(tsne_coords, method = "none", methargs = list(dunkley2006), main = "t-SNE")
highlightOnPlot(tsne_coords, foi = fn, pch = 17, cex = 1.2)
> sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.4
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] pRolocdata_1.34.0 pRoloc_1.36.0 BiocParallel_1.30.3
[4] MLInterfaces_1.76.0 cluster_2.1.3 annotate_1.74.0
[7] XML_3.99-0.10 AnnotationDbi_1.58.0 IRanges_2.30.0
[10] MSnbase_2.22.0 ProtGenerics_1.28.0 S4Vectors_0.34.0
[13] mzR_2.30.0 Rcpp_1.0.8.3 Biobase_2.56.0
[16] BiocGenerics_0.42.0
loaded via a namespace (and not attached):
[1] BiocFileCache_2.4.0 plyr_1.8.7 splines_4.2.0
[4] listenv_0.8.0 GenomeInfoDb_1.32.2 ggplot2_3.3.6
[7] digest_0.6.29 foreach_1.5.2 viridis_0.6.2
[10] fansi_1.0.3 magrittr_2.0.3 memoise_2.0.1
[13] doParallel_1.0.17 mixtools_1.2.0 limma_3.52.2
[16] recipes_0.2.0 globals_0.15.0 Biostrings_2.64.0
[19] gower_1.0.0 hardhat_1.1.0 lpSolve_5.6.15
[22] prettyunits_1.1.1 colorspace_2.0-3 blob_1.2.3
[25] rappdirs_0.3.3 xfun_0.31 dplyr_1.0.9
[28] crayon_1.5.1 RCurl_1.98-1.7 hexbin_1.28.2
[31] impute_1.70.0 survival_3.3-1 iterators_1.0.14
[34] glue_1.6.2 gtable_0.3.0 ipred_0.9-13
[37] zlibbioc_1.42.0 XVector_0.36.0 kernlab_0.9-31
[40] future.apply_1.9.0 scales_1.2.0 vsn_3.64.0
[43] mvtnorm_1.1-3 DBI_1.1.3 viridisLite_0.4.0
[46] xtable_1.8-4 progress_1.2.2 clue_0.3-61
[49] bit_4.0.4 proxy_0.4-27 mclust_5.4.10
[52] preprocessCore_1.58.0 MsCoreUtils_1.8.0 lava_1.6.10
[55] prodlim_2019.11.13 sampling_2.9 httr_1.4.3
[58] FNN_1.1.3.1 RColorBrewer_1.1-3 ellipsis_0.3.2
[61] pkgconfig_2.0.3 nnet_7.3-17 dbplyr_2.2.0
[64] utf8_1.2.2 caret_6.0-92 tidyselect_1.1.2
[67] rlang_1.0.2 reshape2_1.4.4 munsell_0.5.0
[70] tools_4.2.0 LaplacesDemon_16.1.6 cachem_1.0.6
[73] cli_3.3.0 generics_0.1.2 RSQLite_2.2.14
[76] stringr_1.4.0 fastmap_1.1.0 mzID_1.34.0
[79] ModelMetrics_1.2.2.2 knitr_1.39 bit64_4.0.5
[82] purrr_0.3.4 randomForest_4.7-1.1 KEGGREST_1.36.2
[85] dendextend_1.15.2 ncdf4_1.19 future_1.26.1
[88] nlme_3.1-158 xml2_1.3.3 biomaRt_2.52.0
[91] compiler_4.2.0 rstudioapi_0.13 filelock_1.0.2
[94] curl_4.3.2 png_0.1-7 e1071_1.7-11
[97] affyio_1.66.0 tibble_3.1.7 stringi_1.7.6
[100] lattice_0.20-45 Matrix_1.4-1 vctrs_0.4.1
[103] pillar_1.7.0 lifecycle_1.0.1 BiocManager_1.30.18
[106] MALDIquant_1.21 data.table_1.14.2 bitops_1.0-7
[109] R6_2.5.1 pcaMethods_1.88.0 affy_1.74.0
[112] gridExtra_2.3 parallelly_1.32.0 codetools_0.2-18
[115] MASS_7.3-57 gtools_3.9.2.2 assertthat_0.2.1
[118] withr_2.5.0 GenomeInfoDbData_1.2.8 parallel_4.2.0
[121] hms_1.1.1 grid_4.2.0 rpart_4.1.16
[124] timeDate_3043.102 coda_0.19-4 class_7.3-20
[127] segmented_1.6-0 Rtsne_0.16 pROC_1.18.0
[130] lubridate_1.8.0
highlightOnPlot doesn't work when plot2D is used with t-SNE. The features of interest appear in their PCA locations instead of wherever they ended up in the t-SNE plot.
PCA plot with two FOI sets
Same FOI sets, same data, plotted using t-SNE